Customer Analytics

With our customer and product analytics, we answer questions like:

• How big is my potential portfolio cancellation risk?
• What drives my customers to cancel and which levers do I have to avoid for increased effectiveness?
• Who are the top 100 customers I should contact to pitch a promotion?

Selecting the best analytics approach, we predict the likelihood of a customer leaving your company’s services within the next weeks/months. This information can be combined with the overall value of the customer to define the next-best action with one objective in mind – avoiding the loss of an existing and valuable customer.

Our approach and your benefit:

• Provide your customer team with all the relevant information needed to target your customers most effectively
• Help you reduce marketing efforts while increasing customer satisfaction
• Increase your success rate significantly, which will lead to increased revenues for all retained customers

Our advanced cross- and upselling models identify and predict individual preferences based on the customer’s purchasing history. A second analytical model is then used to define the next-best action to target high-value and/or high-potential customers with the right product at the right time.

With this advanced analytics approach, we are able to identify:

• What products, if any, your customer is most willing to buy
• Which customers are most likely to buy another product
• How to convince customers to buy additional products

This customer-analytics method will provide your customer service team with all of the relevant information they need to create a strategic customer segmentation in order to coordinate their marketing activity with focused interventions. The result? Reduced marketing efforts and increased customer satisfaction. Plus, your conversion rate will see a significant increase leading to higher revenues. 

Have you ever asked yourself?

• What revenue will a customer provide in the coming years?
• Who are my high-value and high-potential customers and how can I keep them happy?
• What is the best path to maximise my value for a single customer?

This is where our complex analytics technique really delivers. We answer these questions by creating a segmentation of your portfolio based on the customer lifetime value. This value is a prediction of the net profit attributed to the entire relationship (insured period) with a customer, while in our calculations the focus is on the prediction of the CLV for the upcoming years. We forecast the revenue that every customer will procure to the company up to a defined point in the future.

With our detailed CLV prediction, you instantly gain a better understanding of your customer needs and therefore gain a more comprehensive customer view. The estimation of the net present value of your business also gives you a long-term picture on how to better manage and steer your portfolio and is relevant for all business areas within your company, ranging from product design, marketing and pricing to sales and claims.

We understand that in order to have successfully organised distribution management, you need a solid data foundation and up-to-the-minute monitoring. Munich Re makes sure that all of your company’s relevant data is available, transformed and prepared in actionable visualisations.

Our dynamic, automated and cloud-based web service answers client questions like:

• Which distribution channels are most efficient and effective?
• What does the performance for each channel look like?
• How satisfied are my customers with the service via different channels?

Your benefit:

• Data transformation and processing is taken care of to achieve best results
• Transparency regarding the performance and business coming through each distribution channel is increased
• Actionable insights are gained on customer acquisition visualised in a dynamic way and adjusted to your needs

By leveraging your company’s policy, sales and agent data, we create a strategic customer segmentation for the personalisation of campaigns, website design, policy definition and more. We label these clusters to increase the usability for your marketing department on the respective sales channels, e.g. millennials without cars or leisure seekers (highly risk averse).

This analytics approach will answer your questions on…

• Is there a way to differentiate customers and target them in groups?
• Are there customers more willing to pay than others? If so, who are they and how can they generate more revenues for us?
• Are there potential customers that could provide me with revenue if I were to offer them a slightly lower price?

How this helps you

Target-group optimisation enables your marketing department to approach the right customers at the right point in time and thus improves efficiency and reduces costs. It supports your strategic definition of the best marketing tactics and increases the surplus achievable by every single customer.